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Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...

Protein and Protein Structure

Protein and Protein Structure

Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...

Protein and Protein Structures

Protein and Protein Structures

Conservation of Protein Domains

Conservation of Protein Domains

Protein Folding

Protein Folding

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Updated: Jun 27, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

A Perspective on Protein Structure Prediction Using Quantum Computers.

Hakan Doga¹, Bryan Raubenolt², Fabio Cumbo²

¹IBM Quantum, Almaden Research Center, San Jose, California 95120, United States.

Journal of Chemical Theory and Computation

|May 4, 2024

Summary

This summary is machine-generated.

Quantum computing may accelerate protein structure prediction. Researchers developed a framework to identify suitable problems and demonstrated accurate Zika virus protein loop structure prediction on quantum hardware.

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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Computational Biology
Quantum Computing
Biomedical Research

Background:

Deep learning methods like AlphaFold2 have advanced *in silico* protein structure prediction.
Protein structure prediction remains a significant challenge in biomedical research.
Quantum computing's potential for complex computational problems is increasingly recognized.

Purpose of the Study:

To explore the potential of quantum computing for protein structure prediction.
To develop a framework for selecting protein structure prediction problems amenable to quantum advantage.
To estimate quantum resources required for such problems on utility-scale quantum computers.

Main Methods:

Development of a systematic framework for identifying quantum-advantageous protein structure prediction problems.
Estimation of quantum resource requirements for selected problems on utility-scale quantum computers.
Proof-of-concept validation using quantum hardware to predict a specific protein structure.

Main Results:

Accurate prediction of a catalytic loop structure from the Zika Virus NS3 Helicase using quantum hardware.
Demonstration of the feasibility of the proposed problem selection framework.
Insights into the quantum resources needed for protein structure prediction tasks.

Conclusions:

Quantum computing holds promise for advancing *in silico* protein structure prediction.
The developed framework provides a systematic approach to identifying suitable problems for quantum advantage.
Further research is warranted to fully leverage quantum computing for complex biological problems.